solution

Today is March 30, 2020, and you have just started your new job with a financial planning firm. You have been asked to review a portion of a client’s stock portfolio to determine the risk/return profiles of 12 stocks in the portfolio. Unfortunately, your small firm cannot afford the expensive databases that would provide all this information with a few simple keystrokes, but that’s why they hired you. Specifically, you have been asked to determine the monthly average returns and standard deviations for the 12 stocks for the past six years. In the following chapters, you will be asked to do more extensive analyses on these same stocks. (solution in excel file )

The stocks (with their symbols in parentheses) are:

Archer Daniels Midland (ADM)
Boeing (BA)
Caterpillar (CAT)
Deere & Co. (DE)
General Mills, Inc. (GIS)
eBay (EBAY)
Hershey (HSY)
International Business Machines Corporation (IBM)
JPMorgan Chase & Co. (JPM)
Microsoft (MSFT)
Procter and Gamble (PG)
Walmart (WMT)

1. Collect price information for each stock from Yahoo! Finance (finance.yahoo.com) as follows:
   1. Enter the stock symbol. On the page for that stock, click “Historical Prices” on the left side of the page.
   2. Enter the “start date” as March 1, 2014 and the “end date” as March 30, 2020 to cover the six-year period. Make sure you click “monthly” next to the date; the closing prices reported by Yahoo! will then be for the last day of each month.
   3. After hitting “Get Prices,” scroll to the bottom of the first page and click “Download to Spreadsheet.” If you are asked if you want to open or save the file, click open.
   4. Copy the entire spreadsheet, open Excel, and paste the Web data into a spreadsheet. Delete all the columns except the date and the adjusted close (the first and last columns).
   5. Keep the Excel file open and go back to the Yahoo! Finance Web page and hit the back button. If you are asked if you want to save the data, click no.
   6. When you return to the prices page, enter the next stock symbol and hit “Get Prices” again. Do not change the dates or frequency, but make sure you have the same dates for all the stocks you will download. Again, click “Download to Spreadsheet” and then open the file. Copy the last column, “Adj. Close,” paste it into the Excel file and change “Adj. Close” to the stock symbol. Make sure that the first and last prices are in the same rows as the first stock.
   7. Repeat these steps for the remaining 10 stocks, pasting each closing price right next to the other stocks, again making sure that the correct prices on the correct dates all appear on the same rows.
2. Convert these prices to monthly returns as the percentage change in the monthly prices. (Hint: Create a separate worksheet within the Excel file.) Note that to compute a return for each month, you need a beginning and ending price, so you will not be able to compute the return for the first month.
3. Compute the mean monthly returns and standard deviations for the monthly returns of each of the stocks. Convert the monthly statistics to annual statistics for easier interpretation (multiply the mean monthly return by 12, and multiply the monthly standard deviation by the square root of 12).
4. Add a column in your Excel worksheet with the average return across stocks for each month. This is the monthly return to an equally weighted portfolio of these 12 stocks. Compute the mean and standard deviation of monthly returns for the equally weighted portfolio. Double check that the average return on this equally weighted portfolio is equal to the average return of all of the individual stocks. Convert these monthly statistics to annual statistics (as described in Step 3) for interpretation.
5. Using the annual statistics, create an Excel plot with standard deviation (volatility) on the x-axis and average return on the y-axis as follows:
   1. Create three columns on your spreadsheet with the statistics you created in Questions 3 and 4 for each of the individual stocks and the equally weighted portfolio. The first column will have the ticker, the second will have annual standard deviation, and the third will have the annual mean return.
   2. Highlight the data in the last two columns (standard deviation and mean), choose Insert>Chart>XY Scatter Plot. Complete the chart wizard to finish the plot.
6. What do you notice about the volatilities of the individual stocks, compared to the volatility of the equally weighted portfolio?

Now update the stock portfolio by:

• Rebalancing the portfolio with the optimum weights that will provide the best risk and return combinations for the new 12-stock portfolio.
• Determining the improvement in the return and risk that would result from these optimum weights compared to the current method of equally weighting the stocks in the portfolio.

Use the Solver function in Excel to perform this analysis (the time-consuming alternative is to find the optimum weights by trial-and-error).

1. Begin with the equally weighted portfolio analyzed in Chapter 10. Establish the portfolio returns for the stocks in the portfolio using a formula that depends on the portfolio weights. Initially, these weights will all equal 1/12. You would like to allow the portfolio weights to vary, so you will need to list the weights for each stock in separate cells and establish another cell that sums the weights of the stocks. The portfolio returns for each month must reference these weights for Excel Solver to be useful.
2. Compute the values for the monthly mean return and standard deviation of the portfolio. Convert these values to annual numbers (as you did in Chapter 10) for easier interpretation.
3. Compute the efficient frontier when short sales are not allowed. Use the Solver tool in Excel (on the Data tab in the analysis section).* To set the Solver parameters:
   1. Set the objective to be the cell that computes the (annual) portfolio standard deviation. Minimize this value.
   2. Set the “By Changing Variable Cells” to the cells containing the portfolio weights. (Hold the Control key and click in each of the 12 cells containing the weights of each stock.)
   3. Add constraints by clicking the Add button next to the “Subject to the Constraints” box. The first constraint is that the cell containing the sum of all the portfolio weights must equal one. The next set of constraints is that each portfolio weight is non-negative. You can enter these constraints individually, or check the box “Make Unconstrained Variables Non-Negative.”
   4. Compute the portfolio with the lowest standard deviation. If the parameters are set correctly, you should get a solution when you click “Solve.” If there is an error, you will need to double check the parameters, especially the constraints.
4. Next, compute portfolios that have the lowest standard deviation for a target level of the expected return.
   1. Start by finding the portfolio with an expected return of 2% higher than the annual return for the minimum variance portfolio you computed in Step 3, rounded to the nearest whole percentage. To do this, add a constraint that the (annual) portfolio return equals this target level. Click “Solve” and record the standard deviation and mean return of the solution (and be sure the mean return equals target—if not, check your constraint).
   2. Repeat Step (a) raising the target return in 2% increments, recording the result for each step. Continue to increase the target return and record the result until Solver can no longer find a solution. Next, repeat Step (a) by lowering the target return in 2% increments from the return of the minimum variance portfolio, again recording each result.
   3. At what level does Solver fail to find a solution? Why?
5. Plot the efficient frontier with the constraint of no short sales. To do this, create an XY Scatter Plot , with portfolio standard deviation on the x-axis and the return on the y-axis, using the data for the minimum variance portfolio and the portfolios you computed in step 4. How do these portfolios compare to the mean and standard deviation for the equally weighted portfolio analyzed before?
6. Redo your analysis to allow for short sales by removing the constraint that each portfolio weight is greater than or equal to zero. Use Solver to calculate the (annual) portfolio standard deviation for annual returns in 5% increments from 0% to 40%. Plot the unconstrained efficient frontier on an XY Scatter Plot. How does allowing short sales affect the frontier?
7. Redo your analysis adding a new risk-free security that has a 3% annual return, or 0.25% (0.0025) each month. Include a weight for this security when calculating the monthly portfolio returns. That is, there will now be 13 weights, one for each of the 12 stocks and one for the risk-free security. Again, these weights must sum to 1. Allow for short sales, and use Solver to calculate the (annual) portfolio standard deviation when the annual portfolio returns are set to 3%, 10%, 20%, 40%. Plot the results on the same XY Scatter Plot, and in addition keep track of the portfolio weights of the optimal portfolio. What do you notice about the relative weights of the different stocks in the portfolio as you change the target return? Can you identify the tangent portfolio?

Need the solution in excel file

thank you